Sökning: "radiotherapy treatment planning"

Visar resultat 16 - 20 av 67 uppsatser innehållade orden radiotherapy treatment planning.

1. 16. Domain Adaptation for Combined CT and CBCT Deep Learning Segmentation

   Master-uppsats, Lunds universitet/Matematik LTH

   Författare :Jonas Berg; [2021]
   Nyckelord :CT; CBCT; Deep Learning; Medical Image Segmentation; Radiotherapy; Domain Adaptation; CycleGAN; Domain Adversarial Neural Network; U-Net; Data Augmentation; Machine Learning; Technology and Engineering;

   Sammanfattning : Computed tomography (CT) segmentation models are frequently used within radiotherapy treatment planning, but similar models are not available to the related imaging modality cone beam computed tomography (CBCT) due to the scarcity of labeled data from this domain. Such models could have multiple clinical applications whereby it is of interest to study whether the CT segmentation models can be adapted to generalize to the CBCT domain. LÄS MER

3. 17. Clinical dose feature extraction for prediction of dose mimicking parameters

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Anton Finnson; [2021]
   Nyckelord :Radiation therapy; feature extraction; wavelets; treatment planning; dose mimicking; variational autoencoder; Strålterapi; wavelets; doshärmning;

   Sammanfattning : Treating cancer with radiotherapy requires precise planning. Several planning pipelines rely on reference dose mimicking, where one tries to find machine parameters best mimicking a given reference dose. Dose mimicking relies on having a function that quantifies dose similarity well, necessitating methods for feature extraction of dose images. LÄS MER

4. 18. Monte-Carlo computations of dose distributions for magnetic resonance guided radiotherapy

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/FREIA

   Författare :Claes Fälth; [2021]
   Nyckelord :Radiotherapy; MRgRT;

   Sammanfattning : The goal with radiotherapy is to damage tumour cells with ionizing radiation while minimizing radiation to healthy tissue. In recent years magnetic resonance guided radiotherapy has become increasingly popular. With this technique a magnetic resonance image of the patient anatomy is obtained in connection with the treatment session. LÄS MER

5. 19. Deep-learning based prediction model for dose distributions in lung cancer patients

   Master-uppsats, Stockholms universitet/Fysikum

   Författare :Terese Hellström; [2021]
   Nyckelord :;

   Sammanfattning : Background To combat one of the leading causes of death worldwide, lung cancer treatment techniques and modalities are advancing, and the treatment options are becoming increasingly individualized. Modern cancer treatment includes the option for the patient to be treated with proton therapy, which can in some cases spare healthy tissue from excessive dose better than conventional photon radiotherapy. LÄS MER

7. 20. Evaluation of margins and plan robustness for proton therapy of unilateral tonsil cancer.

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för fysik; Umeå universitet/Institutionen för strålningsvetenskaper

   Författare :Josefine Grefve; [2021]
   Nyckelord :;

   Sammanfattning : During proton therapy both target volumes and healthy tissue, including organs at risk (OARs), receives radiation dose. Thus, radiotherapy is a trade-off between good target coverage and OAR sparing. For protons, most of the dose is deposited right before it is stopped, a phenomenon termed the Bragg peak. LÄS MER